whisper-medium-afrispeech-clinical
This model is a fine-tuned version of openai/whisper-medium on the afrispeech-200 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7878
- Model Preparation Time: 0.0098
- Wer: 0.136
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2239
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer |
|---|---|---|---|---|---|
| 0.4946 | 1.0 | 2240 | 0.5593 | 0.0098 | 0.157 |
| 0.3420 | 2.0 | 4480 | 0.5074 | 0.0098 | 0.144 |
| 0.1856 | 3.0 | 6720 | 0.5242 | 0.0098 | 0.147 |
| 0.1157 | 4.0 | 8960 | 0.5676 | 0.0098 | 0.142 |
| 0.0364 | 5.0 | 11200 | 0.6216 | 0.0098 | 0.139 |
| 0.0184 | 6.0 | 13440 | 0.6494 | 0.0098 | 0.137 |
| 0.0066 | 7.0 | 15680 | 0.6938 | 0.0098 | 0.137 |
| 0.0021 | 8.0 | 17920 | 0.7283 | 0.0098 | 0.137 |
| 0.0010 | 9.0 | 20160 | 0.7650 | 0.0098 | 0.135 |
| 0.0006 | 10.0 | 22400 | 0.7878 | 0.0098 | 0.136 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.4.1+cu121
- Datasets 2.19.0
- Tokenizers 0.22.2